Summary

1. Maintaining viable populations in different habitats requires physiological, morphological and demographic adaptations of plants. In sandland environments, plants experience substantial variation in growing conditions during the dune fixation process, with high sand mobility in early stages and denser vegetation cover in later stages.

2. We studied the changes in demography of a dominant shrub, Artemisia ordosica, at three stages of dune fixation: semi-fixed dunes, fixed dunes and fixed dunes covered with microbiotic crust. Demographic data from three annual censuses were used to parameterize integral projection models (IPMs) to conduct comparative demographic analyses.

4. Elasticity analysis revealed that survival was a key vital rate for population growth in all habitats. Growth and fecundity were of higher importance in the semi-fixed habitat than in the other two habitats where shrinkage became an important factor determining λ. Seedlings and small plants were critical for population growth in semi-fixed dunes, whereas moderate to large-sized plants were most important in the other habitats.

5. Results of life table response experiments showed that the observed strong decrease in λ during dune fixation was mainly caused by reduction in fecundity, but with additional and considerable contributions from reduced plant growth and increased occurrence of shrinkage. Thus, populations in semi-fixed dunes are able to expand rapidly due to a much higher fecundity compared to those in other habitats.

6.Synthesis. Artemisia ordosica adopts different life history strategies along the dune fixation process. Fast expansion in semi-fixed dunes is enabled by high seed production and effective recruitment, while populations at later dune fixation stages are maintained through frequent plant shrinkage. Integral projection models are highly appropriate tools for analysing such life history changes as they are based on statistical comparisons of vital rates across habitats.

Inland dune ecosystems contain very distinct habitat types, ranging from mobile dunes – in which sand burial and denudation are commonplace – to fixed dunes covered with a microbiotic crust layer that inhibits water penetration to deeper soil level (Eldridge & Greene 1994; Kobayashi, Liao & Li 1995; Li et al. 2010a). Long-lived woody shrubs – which are common in some dune ecosystems – need to cope with such strongly varying environmental conditions along their lifetime and across habitats (Kobayashi, Liao & Li 1995; Li 2001). At the early stages of the dune fixation process, seedling survival and growth are strongly limited by sand movement (Li et al. 2010a, b). At later stages in this process, the denser vegetation cover and microbiotic crust layer are expected to limit growth of the larger deep-rooted individuals (Eldridge & Greene 1994; Li et al. 2006; Zuo et al. 2009). It has been observed that many shrub species are able to colonize dunes in the early stages of dune fixation, although some can dominate more stages (Kobayashi, Liao & Li 1995; Bai et al. 2008). So far, however, we do not know what drives the colonization, stabilization and decline of woody plant populations along the dune fixation process.

Dune plants often have the ability to cope with drought stress by size shrinking, branch loss or stem splitting (Schenk 1999; Salguero-Gomez & Casper 2010). These processes are often neglected in plant demographic studies, although they may contribute greatly to population maintenance (Salguero-Gomez & Casper 2010). Classical matrix models, which are often used to study the demography of plants, offer limited possibilities to include strong variation in growth (such as shrinkage; Zuidema et al. 2010). Integral projection models (IPMs), an extension of matrix models, allow for explicit inclusion of growth variation and can therefore be particularly useful for analysing the demography of dune plants (Easterling, Ellner & Dixon 2000).

We used IPMs to compare the population dynamics of a dominant shrub, Artemisia ordosica, across stages of dune fixation in Mu Us Sandland, in Inner Mongolia, China. Artemisia ordosica occurs sparsely in mobile dunes and can dominate semi-fixed dunes, fixed dunes and fixed dunes covered with microbiotic crust, with the highest abundance in fixed dunes (Kobayashi, Liao & Li 1995; Li et al. 2010a). Reduced seed production and partial death of branches are often observed in A. ordosica populations at later dune fixation stages (Kobayashi, Liao & Li 1995; Guo 2000). However, it is still unknown to what extent population growth rates in fixed dunes are affected by these changes in vital rates. Specifically, we address the following questions: (i) What are the differences in vital rates (survival, growth and reproduction) of A. ordosica at different stages of dune fixation? We expected seedling survival and growth would be lower at early dune fixation stages because of frequent sand burial and removal events, while adults were expected to have a poorer performance at later dune fixation stages due to increased water shortage at deeper soil levels. (ii) To what extent do population growth rates differ across dune fixation stages? We expected strong population increase in early stages and projected population decline in late phases. (iii) Which demographic components play critical roles for population growth, and do they vary across dune fixation stages? (iv) What differences in vital rates explain variation in population growth across dune fixation stages?

Materials and methods

Study species and area

Artemisia ordosica Krasch (Asteraceae) is a shrub with plumose, linearly lobate leaves (Kobayashi, Liao & Li 1995). Its root system is mainly distributed in the upper 30 cm of the sand, while its main roots may reach 1–3 m deep (Li et al. 2010b). This species is overwhelmingly dominant in the Mu Us Sandland on semi-fixed dunes, fixed dunes and fixed dunes covered with microbiotic crust. Recruitment is generally realized by reproduction from seed (Huang & Gutterman 2000), although plants may occasionally split into clonal fragments (Schenk 1999). Plants start reproducing at the age of 2–3 years. Seeds set in August and mature in October. Reproductive shoots die in winter, while woody vegetative shoots survive the winter and generate new vegetative or reproductive shoots in the next spring (Li et al. 2010b).

This study was conducted at Ordos Sandland Ecological Station (OSES, 39°29’37.6’’ N, 110°11’29.4’’ E) of Institute of Botany of Chinese Academy of Sciences, located in the north-eastern Mu Us Sandland in Inner Mongolia, China. Mu Us Sandland is a semi-arid area of 39 800 km2, with a mean annual precipitation of 260–450 mm, which is mainly concentrated in summer (Zhang 1994). Annual rainfall during our two census periods was quite similar, but the rainfall during the main growing season in the first period was higher by 30% than that in the second period (data from KNMI Climate Explorer, http://climexp.knmi.nl/get_index.cgi). Mean annual temperature is 7.5–9.0 °C, with a maximum of 20–24 °C in July and a minimum of −8 to −12 °C in January (Zhang 1994). Most plant species in this area are forbs and grasses, although woody plants may dominate vegetations locally. The main shrub species are A. ordosica, Hedysarum laeve, Salix psammophila and Sabina vulgaris (Li et al. 2010a). These species comprise a large proportion of the total vegetation coverage and fix the sand dunes to different extents (Bai et al. 2008). Microbiotic crust is commonly found on the surface of well-fixed dunes in this study area.

Study design and data collection

Three dune fixation stages, i.e. semi-fixed dunes (SF), fixed dunes (F) and fixed dunes covered with microbiotic crust (FC), were selected. These habitats were located at 2–4 km distance from each other. The total vegetation coverage was 40.1 ± 1.4% (mean ± SE), 62.04 ± 1.0% and 59.26 ± 1.0% in SF, F and FC habitat, respectively. In July 2007, three permanent plots were established in each habitat. The distance between plots within habitats ranged from 500 to 1000 m. Plots measured 20 × 20 m in SF and F habitats and 40 × 40 m in FC habitat, where seedling density was quite low. All plots were then divided into 4 × 4 m subplots. Plants shorter than 10 cm in SF and F habitats and plants taller than 20 cm in F and FC habitats were measured in 4, 4, 10 and 9 randomly selected subplots, respectively. Plants of other sizes were measured in the entire plots. Sub-sampling was done to gain an even distribution of all plant sizes in each plot. In total, data from 6939 individuals were collected during three censuses, one each in July of 2007, 2008 and 2009.

At the first census, total height was measured for each individual. For individuals taller than 20 cm, the two largest perpendicular diameters of the plant’s crown were also measured. Reproductive status was recorded for each individual. The number of inflorescences was assessed into five categories, with the average amounting to 5, 15, 35, 75 and 150 inflorescences, respectively. Upon first measurement, each plant was labelled and its coordinates within the plot were recorded. In 2008 and 2009 the survival of all the labelled plants was checked, and the surviving plants were re-measured, reproductive status was recorded and new recruits were searched and measured.

Statistical analyses

We performed preliminary statistical analyses to compare the suitability of three measures of size for our models: height, crown area and crown volume. As plant height explained more variation in vital rates (survival, growth and reproduction) than the other two measures, we used height to characterize plant size in all analyses and models.

We tested for differences in vital rates among the three plots per habitat for each period using ancova for height growth and logistic regressions for survival and flowering probabilities (height as covariable in both cases). As we found no differences in plant growth among plots (P > 0.05), and just two and five cases of significant differences (P < 0.05) in flowering and survival among plots, respectively (during second census period), we decided to pool the data from all plots within each habitat for subsequent analyses.

We also tested for temporal differences in vital rates in each habitat, using paired t-tests for growth, and logistic regressions for survival and flowering probabilities. Differences between periods were found for all vital rates (paired t-tests and logistic regressions, P < 0.01), except for growth in fixed dunes. We therefore fitted statistical models for both periods separately.

We used multiple regression models to relate future height (y, at t + 1), survival and reproduction to the current height (x, at t) of an individual and to habitat (coded as dummy values with SF habitat as control). The probabilities of survival s(x) and flowering pf(x) were modelled as logistic regressions, with height (x) and habitats as independent variables. Size change (g(y, x)) was tested using multiple linear regression models with future height (y) as independent variable against current height (x) and habitat. Subsequently, variances of that regression were again related to x and habitats in another multiple linear regression. The number of inflorescences fn(x) was related to x and habitats in a multinomial logistic regression, as it was recorded as categories (Poorter et al. 2005).

Integral projection models

We analysed the population dynamics of A. ordosica using IPMs, which describe how a continuously size-structured population changes in discrete time (Easterling, Ellner & Dixon 2000). In IPMs, the state of the population at time t is described by a distribution function n(x, t) and n(x, t)dx represents the number of individuals with size in the range [x, x + dx]. The population dynamics is then written as:

((eqn 1))

where [L, U] is the range of all possible sizes, p(y, x) represents survival and growth from size x to size y and reproduction f(y, x) represents the number of new births of size y at t + 1 produced by an adult of size x at t. p(y, x) was calculated as p(y, x) = s(x)g(y, x) and f(y, x) as f(y, x) = pf(x)fn(x)pefd(y), where pe is the mean number of seedlings produced per inflorescence, and fd(y) is the size distribution of seedlings. p(y, x) + f(y, x) is called the kernel, k(y, x), a non-negative surface representing all possible transitions from size x to size y.

The kernel k(y, x) can be transformed into a large transition matrix K(y, x) with w categories, using the midpoint rule (Easterling, Ellner & Dixon 2000). The dynamics of the population can then be described as in a classical matrix model: n(t + 1) = Kn(t), that can yield the same output as matrix models: population growth rate (λ), sensitivity and elasticity (Ellner & Rees 2006). We used 100 mesh points, because λ values in all populations hardly changed any more when further increasing the number of mesh points. Because we found significant differences between periods and habitats, we constructed IPMs for each census period and habitat, resulting in six IPMs.

Confidence intervals for λ were calculated by bootstrapping (Jongejans et al. 2010). For each bootstrap estimate, we resampled with replacement from the data sets (n = 2487, 2438 and 2014 in SF, F and FC habitats, respectively), re-calculated regression coefficients, established the kernel and calculated λ. This was repeated 5000 times and the 95% confidence intervals for λ were obtained from the frequency distribution of these values.

To examine how far the observed size distribution was from the expected, stable stage structures resulting from IPMs were compared to observed population structures (mean of three plots for each habitat), using the percentage similarity index (PS; Horvitz & Schemske1995): PS = Σ(min[obsi, ssdi]) × 100, where obsi and ssdi are vectors of observed population structures and stable size distributions, respectively (both vectors scaled to sum to 1). High values of this index indicate a high level of similarity (Zuidema, de Kroon & Werger 2007).

To examine the relative importance of transition elements and vital rates to population growth λ, we conducted elasticity analyses (de Kroon, van Groenendael & Ehrlen 2000). We first performed elasticity analysis of matrix elements, in which survival is contained in growth and shrinkage transitions (de Kroon, van Groenendael & Ehrlen 2000; Caswell 2001). Then, to specifically examine the importance of each vital rate (survival, growth, shrinkage and reproduction), we performed vital rate elasticity analyses (Zuidema & Franco 2001). Sensitivities of vital rates in each size category can be calculated as: Survival:

((eqn 2))

Positive growth (for i > j):

((eqn 3))

Negative growth (for i < j):

((eqn 4))

Fecundity:

((eqn 5))

where σj, γij, ρij and fij represent the vital rates of survival, positive growth, negative growth and fecundity, respectively, while Pj, Gij, Rij and Fij represent transition elements for stasis, progression, retrogression and fecundity, respectively. Note that in eqns 3 and 4, the summation over i is done to take into account growth from category j to all categories i that represent positive growth (i > j) or negative growth (i < j). In eqn 5, the summation over i is done to include new seedlings of all sizes. Note also that eqns 3 and 4 allow negative values for sensitivity in the case that the element sensitivity of stasis (Pj) is larger than that of growth (Gij for eqn 3) or shrinkage (Rij for eqn 4, Zuidema & Franco 2001). Elasticities of vital rates can then be calculated as:

((eqn 6))

where xij is the value of vital rate under consideration (σj, γij, ρij and fij).

Differences in population growth rates among habitats or periods may be caused by variation in vital rates across habitats and periods. Analysis of life table response experiment (LTRE) allows quantification of the contribution of each element or vital rate to the observed difference in population growth rate (Caswell 2001; Jongejans & de Kroon 2005). We conducted a fixed-design LTRE on vital rates to evaluate the contribution of variation in vital rates to differences in population growth rate (Yamada et al. 2007). The two-factor LTRE analysis is as follows:

((eqn 7))

where λ of habitat m and period n is calculated as the sum of λ for the overall mean matrix, λ(··), the effect of habitat m, α(m), the effect of period n, β(n), and the residual ‘interaction’ effect (αβ)(mn). First, the main effects were estimated separately, while ignoring the interaction term (Caswell 2001; Jongejans & de Kroon 2005):

((eqn 8))

((eqn 9))

where differences between the value of a vital rate aij(m.) of the mean-habitat matrix K(m.) or aij(.n) of the mean-period matrix K(.n) and the overall mean vital rate aij(..) of matrix K(··) are multiplied by the sensitivity values of the matrix halfway between the matrix of interest and the overall mean matrix (Yamada et al. 2007). The interaction effect (αβ)(mn) is then calculated as (Jongejans & de Kroon 2005):

Results

Vital rates in relation to size, habitat and census period

Survival probability of A. ordosica individuals increased with height (Table 1, Fig. 1a and b), from 36% for seedlings of 5 cm high to 94% for large adults of 40 cm height on average. Survival chance also differed among habitats, with lower values in the fixed dunes (F), especially for the small individuals (Fig. 1a and b).

Table 1. Statistical models and parameter estimates used to construct the kernel for the integral projection model of Artemisia ordosica in Mu Us Sandland during two census periods (1: 2007–2008 and 2: 2008–2009)

Demographic process

Period

Model

The models are functions of plant height (x), habitats (F and FC) and interactions between height and habitat (x_F, x_FC), using the semi-fixed dune habitat (SF) as a reference. F and FC represent habitats of fixed dunes and fixed dunes covered with microbiotic crust, respectively. Values in parentheses are standard errors of parameter estimates.

Survival probability (s)

1

SF: Logit(s) = −0.81(0.07) + 0.10(0.01)x

F: Logit(s) = −1.26(0.11) + 0.12(0.01)x_F

FC: Logit(s) = −0.81(0.07) + 0.10(0.01)x_FC

n = 4224, R2 = 0.53, P <0.0001

2

SF: Logit(s) = −1.46(0.10) + 0.10(0.01)x

F: Logit(s) = −1.46(0.10) + 0.09(0.01)x_F

FC: Logit(s) = −0.67(0.11) + 0.08(0.01)x_FC

n = 4739, R2 = 0.46, P <0.0001

Flowering probability (pf)

1

SF : Logit(pf) = −5.16 (0.30) + 0.13(0.01)x

F : Logit(pf) = −4.04 (0.35) + 0.10(0.01)x_F

FC : Logit(pf) = −3.93 (0.39) + 0.11(0.01)x_FC

n = 4224, R2 = 0.73, P <0.0001

2

SF : Logit(pf) = −5.43 (0.17) + 0.14(0.01)x

F : Logit(pf) = −5.43 (0.17) + 0.13(0.00)x_F

FC : Logit(pf) = −5.43 (0.17) + 0.10(0.00)x_FC

n = 4739, R2 = 0.76, P <0.0001

Future size (ŷ)

1

SF: 8.75(0.36) + 0.89(0.01)x

F: 5.80 (0.42) + 0.89(0.01)x_F

FC: 8.75(0.36) + 0.74 (0.01)x_FC

n = 2813, R2 = 0.83, P <0.0001

2

SF: ŷ = 7.74(0.31) + 0.89(0.01)x

F: ŷ = 7.74(0.31) + 0.82(0.01)x_F

FC: ŷ = 7.74(0.31) + 0.78(0.01)x_FC

n = 2872, R2 = 0.83, P <0.0001

Variance of growth (σ2)

1

SF: σ2 = 19.42(6.79) +1.94(1.53)x

F: σ2 = 19.42(6.79) +1.94(1.53)x_F

FC: σ2 = 19.42(6.79) +1.94(1.53)x_FC

n = 2813, R2 = 0.05, P <0.0001

2

SF: σ2 = 1.95(0.14)x

F: σ2 = 1.95(0.14)x_F

FC: σ2 = 2.94(0.18)x_FC

n = 2872, R2 = 0.08, P <0.0001

Figure 1. Relations of vital rates with height for Artemisia ordosica in Mu Us Sandland during 2007–2008 (a, c, e and g) and 2008–2009 (b, d, f and h) and in three dune habitats (Semi-fixed, Fixed and Fixed-crust). Regression functions are given in Table 1.

Large individuals grew more slowly than small ones, as indicated by the regressions with slopes of <1 (Table 1). Many individuals showed negative growth, i.e. shrinkage in size. Shrinkage was particularly strong for large individuals (Fig. 1c and d). Height growth differed between habitats in both periods (Table 1). For plants taller than 20 cm, height growth declined strongly as the dunes were more fixed, with the highest value in SF habitat, lowest in FC habitat and intermediate in F habitat (Fig. 1c and d). For small plants shorter than 20 cm, the pattern was somewhat different, with a higher growth in FC habitat compared to F habitat in the first census period (Fig. 1c). Residuals from the growth regression models in each period had a normal distribution and growth variance showed a positive relation with plant height (Table 1).

Flowering probability increased with height (Table 1), and about 50% of individuals of 40–60 cm high were reproductive. Flowering probability showed similar patterns among habitats in the first census period (Fig. 1e), but was lower in FC habitat than in SF and F habitats during the second census period (Fig. 1f). Number of inflorescences, i.e. the second component of fecundity, was highly variable across individuals. Individuals of the same height could bear from few to more than 100 inflorescences (Fig. 1g and h). Despite this variation, number of inflorescences increased with height (Table 2). Inflorescence production differed greatly among habitats and was much lower in FC habitat than in the other two habitats (Fig. 1g and h). The number of seedlings per inflorescence (pe) was much higher in SF habitat than in F and FC habitats in both census periods (Table 2).

Table 2. Statistical models and parameter estimates describing the number of seedlings per inflorescence (pe) and seedling height distribution (fd(y)) of Artemisia ordosica in three habitats during two census periods (1: 2007–2008 and 2: 2008–2009)

Habitat

Demographic process

Period

Model

Semi-fixed (SF)

pe

1

0.239

2

0.151

fd(y) (cm)

1

Gaussian with mean = 4.50, Variance = 3.69, truncated at 0, n = 665

2

Gaussian with mean = 4.65, Variance = 4.64, truncated at 0, n = 302

Fixed (F)

pe

1

0.003

2

0.009

fd(y) (cm)

1

Gaussian with mean = 5.64, Variance = 6.46, truncated at 0, n = 21

2

Gaussian with mean = 4.64, Variance = 3.87, truncated at 0, n = 34

Fixed-crust (FC)

pe

1

0.025

2

0.021

fd(y) (cm)

1

Gaussian with mean = 5.73, Variance = 10.36, truncated at 0, n = 697

2

Gaussian with mean = 5.20, Variance = 6.89, truncated at 0, n = 262

The resulting kernels showed large differences among habitats in both census periods, with more positive growth and higher fecundity transitions in SF habitat than in F and FC habitats and more shrinkage transitions in FC and F habitats than in SF habitat (Fig. 2).

Figure 2. Fitted kernels of transitions for Artemisia ordosica in Mu Us Sandland during 2007–2008 (a–c) and 2008–2009 (d–f) in semi-fixed dunes (a and d), fixed dunes (b and e) and fixed dunes covered by microbiotic crust (c and f). Transition values are shown for transitions from present size (x-axis) to future size (y-axis). Grey tones indicate the magnitude of the transitions with values >0.06 shown in white. Transitions along the diagonal represent survival–growth transitions, while those on the bottom correspond to recruitment.

Population growth rates and stable structures

Population growth rates (λ) of A. ordosica showed large variation among habitats and moderate variation between census periods (Table 3). Population growth varied from rapid increasing (λ > 1) in SF habitat to declining (λ < 1) in F habitat and especially in FC habitat (Table 3), and λ was smaller in the second than in the first census period (Table 3). The temporal differences in F and FC habitats were much smaller than in SF habitat (Table 3).

Table 3. Population growth rates (λ) and 95% confidence intervals of Artemisia ordosica in Mu Us Sandland in three habitats, during two census periods

Habitat

Period

2007–2008

2008–2009

Semi-fixed (SF)

1.355 [1.294, 1.405]

1.088 [1.057,1.125]

Fixed (F)

0.979 [0.961,0.991]

0.913 [0.890, 0.935]

Fixed-crust (FC)

0.936 [0.911,0.961]

0.888 [0.864, 0.916]

The stable size structure was characterized by a high proportion of seedlings and small plants <20 cm in SF habitat, while the structure was dominated by individuals of 20–60 cm high in FC habitat (Fig. 3). The stable size distributions resembled the observed size structure better in SF and FC habitats than in F habitat. Similarity reached over 70% in SF and FC habitats but was smaller than 50% in F habitat (Fig. 3).

Elasticity analyses

We performed two types of elasticity analyses: one for the elements in the transition matrix and the other for the underlying vital rates. Elasticity analyses of elements showed that survival–growth and survival–shrinkage transitions held the largest proportion of elasticity while elasticity of fecundity transitions was relatively small (Fig. 4). The element elasticity varied greatly across habitats: elasticities of survival–growth transitions and fecundity were the highest in SF habitat and lowest in FC habitat, while elasticity of survival–shrinkage transitions showed the opposite pattern (Fig. 4). The distributions of element elasticity across size categories also differed greatly among the three habitats: it was more evenly distributed in SF habitat where seedlings and small individuals had the greatest proportional elasticity (Fig. 4a and d) than in F habitat (Fig. 4b and e) where large plants were dominant or in FC habitat where intermediate-sized plants were dominant (Fig. 4c and f).

Figure 4. Elasticity of population growth rate to transitions for Artemisia ordosica in Mu Us Sandland during 2007–2008 (a–c) and 2008–2009 (d–f) in semi-fixed dunes (a and d), fixed dunes (b and e) and fixed dunes covered by microbiotic crust (c and f). Elasticity values are shown for transitions from present size (x-axis) to future size (y-axis). Grey tones indicate the magnitude of the elasticity; values >0.002 are shown in white.

Vital rate elasticity clearly showed that survival was more important than other vital rates for population growth. This was the case for both census periods and all three habitats (Fig. 5). Elasticity of shrinkage was negative in all populations, indicating a negative effect on population growth (Fig. 5). Vital rate elasticity differed strongly among habitats: growth and fecundity elasticity were much higher in SF (Fig. 5a and d) than in the other two habitats (Fig. 5b, c, e and f). Shrinkage elasticity as measured by absolute value was much higher in F (Fig. 5b and e) and FC (Fig. 5c and f) than in SF habitat (Fig. 5a and d). In F and FC habitats values of shrinkage elasticity were close to those of growth elasticity, suggesting that shrinkage was of similar importance for population growth in the later stages of dune fixation (Fig. 5).

Life table response experiments

Our LTRE analysis showed that habitat differences caused stronger variation in λ than temporal differences (Table 4). The strong variation in λ across habitats was attributed mainly to fecundity (contributing to 51% of the total variation), and to a lesser extent to growth (22%) and shrinkage (17%). Despite the high values of survival elasticity, variation in survival contributed the least (10%) to the variation in λ across habitats.

Table 4. Effects of habitat, census period and their interaction on variation in population growth rate of Artemisia ordosica, based on life table response experiments (LTREs)

LTRE effect

The mean and standard deviation of the absolute values for the main effects and interactions are also shown.

Habitat (α)

Semi-fixed

0.174

Fixed

−0.087

Fixed-crust

−0.121

Mean ± SD of | αm |

0.127 ± 0.044

Census period (β)

2007–2008

0.072

2008–2009

−0.066

Mean ± sd of | βn |

0.069 ± 0.005

Interaction between habitat and census period (αβ)

Semi-fixed × 2007–2008

0.108

Fixed × 2007–2008

0.003

Fixed-crust × 2007–2008

−0.001

Semi-fixed × 2008–2009

−0.094

Fixed × 2008–2009

−0.005

Fixed-crust × 2008–2009

0.011

Mean ± SD of | αβmn |

0.037 ± 0.045

Compared to the average population growth of all habitats, λ in SF habitat was considerably higher, while that in both F and FC habitats were lower (Table 4). In SF habitat all vital rates, except shrinkage in the plants below 20 cm, contributed positively to the differences in λ (Fig. 6c). Shrinkage also contributed positively to the change in λ in SF habitat, because shrinkage was little in this habitat. By contrast, in F and FC habitats almost all vital rates contributed negatively to the change in λ, except that shrinkage showed a small positive contribution in F habitat and survival in plants shorter than 20 cm showed a positive contribution in FC habitat (Fig. 6d and e).

Figure 6. Results of analyses of Life Table Response Experiments (LTREs) for Artemisia ordosica in Mu Us Sandland. Shown are the contributions of vital rates to temporal variation in population growth for 2007–2008 (a) and 2008–2009 (b) and contributions to variation in population growth across habitats for semi-fixed dunes (c), fixed dunes (d) and fixed dunes covered by microbiotic crust (e).

The effect of census period on λ was positive in the first period (2007–2008) and negative in the second period (2008–2009; Table 4). The positive effect in the first period was mainly due to the higher survival of small and middle-sized plants (shorter than 60 cm), as well as the higher fecundity of the reproductive plants; the reverse was the reason for the negative effect in the second census period (Fig. 6a and b).

The sum over all LTRE contributions from all vital rates differed by only 5.6% from the observed change in λ, indicating that LTRE provided good estimates for the effects of habitats and census periods on λ.

Discussion

Differences in vital rates among habitats

Vital rates of A. ordosica differed substantially among stages of dune fixation. Individuals in semi-fixed dunes generally showed much higher growth and fecundity compared to those in the fixed dunes and the fixed dunes with microbiotic crust. The exception to this overall pattern was that seedlings showed a poorer performance in semi-fixed dunes than in fixed dunes with microbiotic crust. The frequent sand deposition in semi-fixed dunes may differentially affect plants of different sizes (Li et al. 2010a, b). While moderate sand burial can benefit plants by increasing water and nutrient availability, deep burial may impose pressure on plants by creating a physical barrier for vertical growth and reducing the photosynthetic area (Brown 1997; Shi et al. 2004; Li et al. 2010a, b). The sand deposition regime in semi-fixed dunes may thus have resulted in moderate burial of A. ordosica adult plants, stimulating growth and reproduction, while impeding seedling performance by deep or complete burial (Li et al. 2010a,b).

The lower growth and reproduction rates of large A. ordosica individuals in the later dune fixation stages may be caused by increased plant density and reduced soil water content in these stages (Miriti, Wright & Howe 2001; Zuo et al. 2009). The formation of a microbiotic crust is likely to be another cause of the poor performance of large plants. A microbiotic crust greatly reduces water availability in deep soil layers by interception of rainfall in the upper soil layer and subsequent evapotranspiration (Eldridge & Greene 1994; Li et al. 2006). While this may negatively affect the performance of the deep-rooting large A. ordosica individuals, it may promote survival and growth of the more shallowly rooted seedlings.

A high proportion of the A. ordosica individuals exhibited shrinkage, particularly in the larger size classes and in the fixed dunes with microbiotic crust. Shrinkage in height was mainly caused by the (partial) death of branches. Shrinkage is a common phenomenon in long-lived desert plants and may promote survival under unfavourable growing conditions (Salguero-Gomez & Casper 2010). Another adaptation to prolonged drought is stem splitting (Werger 1986), which is known to occur in A. ordosica (Schenk 1999), but was not assessed in our study. The increased incidence of shrinkage in fixed dune habitats was likely caused by reduced water availability due to the higher plant density and the formation of microbiotic crust. Shrinkage and splitting are likely adaptive strategies that allow large A. ordosica individuals to survive and populations to maintain themselves in the later stages of the dune fixation process.

Differences in population dynamics across habitats

Population growth of A. ordosica declined greatly as the dunes were more fixed, from fast growth (λ = 1.35–1.09) in SF to moderate decline in FC (λ = 0.94–0.89). Such differences among habitats are consistent with the observed density pattern of A. ordosica populations, which increases at early dune fixation stages, peaks in fixed dunes and then decreases again in later stages. Population growth rate varied much more strongly across habitats than between periods and was exceptionally high for a long-lived shrub species. Usually population growth rates of long-lived shrubs are close to unity and do not show large variation across habitats (Silvertown et al. 1993; Bullock, Silvertown & Hill 1996; Watson, Westoby & Holm 1997; Kyncl et al. 2006). Thus, the high level of variation in λ suggests a strong effect of dune fixation process on the population dynamics of A. ordosica.

If population growth differs strongly across habitats, is it also governed in a highly habitat-specific way? Our results suggest that this is indeed the case. The distribution of elasticity values over vital rates varied considerably across habitats. While survival was the most important vital rate for population growth in all habitats, its relative importance increased substantially in later dune fixation stages. In these stages, the influence of plant shrinkage was the strongest, while plant growth and fecundity had the highest elasticity in earlier stages of dune fixation. Because growth and fecundity together represent the reproductive pathway, it is not surprising that high growth and fecundity boost population growth at early dune fixation stages (de Kroon, van Groenendael & Ehrlen 2000). Overall, our results suggest that the higher population growth of A. ordosica at early dune fixation stages depends more on high growth and fecundity, and this dependency shifts to survival in later dune fixation stages.

While the adaptive value of shrinkage at individual level is clear – shrinking in size to survive stressful periods – the interpretation of the demographic contribution of shrinkage is less straightforward. Elasticity of shrinkage was generally negative in our study species as well as in others (Salguero-Gomez & Casper 2010). These negative values are caused by the fact that in most cases plant survival and reproductive output increase with size, such that shrinking plants are moving to classes in which they have a lower contribution to population growth. The negative shrinkage elasticity suggests that population growth would increase if the incidence of shrinkage declines. But such simplistic interpretation denies the covariance of vital rates: if plants would not be able to shrink under stressful conditions, their mortality risk would increase. To test this, we performed a simulation to evaluate what will happen to the populations if all plants that exhibited shrinkage would die instead. The projected population growth rates for these simulations show very strong reductions in population growth: from 1.35 to 1.03 in semi-fixed dunes, from 0.98 to 0.53 in fixed dunes and from 0.94 to 0.49 in fixed dunes with microbiotic crust. Although this simple analysis probably provides an overestimate of the adaptive effect of shrinkage, it does suggest that shrinkage in late dune fixation stages allows the declining populations at late dune fixation stages to persist longer by extending the life span of adult plants.

What caused the large differences in population growth across habitats? Analysis of LTREs revealed that variation in population growth was mainly the result of differences in fecundity across habitats. These fecundity differences were likely due to strong variation in seedling recruitment, a factor that is known to be a critical driver of population decline (Rees et al. 2001; Brys et al. 2004; Koop & Horvitz 2005; Jacquemyn, Brys & Jongejans 2010). In our study, the low seedling recruitment in the later stages of dune fixation was likely due to lower rates of seed production and/or of seedling recruitment. In fixed dunes, seedling recruitment rate was 17–80 times lower than in semi-fixed dunes while seed production rate was comparable to that in semi-fixed dunes. In fixed dunes with microbiotic crust, seed production was considerably lower, but seedling recruitment rate had intermediate values. Those intermediate values may be caused by exchange of seeds across habitats, as the various dune fixation stages occur in a mosaic pattern in the landscape. To a lesser extent, variation in population growth rates was caused by differences in growth and shrinkage. Interestingly, variation in survival – the most important vital rate for population maintenance – did not contribute to the variation in population growth.

Integral projection models proved to be very suitable for our comparative demographic study, as they allow the explicit incorporation of strong growth variation exhibited by A. ordosica. Also, the significant habitat effects evaluated in regression models can be directly included in the kernel. The analyses of LTREs are straightforward for IPMs, and provide clear insights into the causes of varying population growth rates among habitats. We therefore recommend using IPMs in comparative plant demographic studies, especially when these involve species with highly varying growth rates.

Demographic adaptations to dune fixation

Our results suggest that A. ordosica adjusts its life history traits to adapt to changing growing conditions during the dune fixation process. At early stages of dune fixation, A. ordosica life history is characterized by high fecundity and rapid growth, resulting in a fast population growth and a typical ‘invasive’ population structure with high proportion of seedlings and juveniles (Oostermeijer, van’t Veer & den Nijs 1994; Rees et al. 2001; Koop & Horvitz 2005). When dunes become fixed, populations of A. ordosica are more or less ‘stable’ in terms of plant density and population growth rate, and the population structure is dominated by larger plants (Oostermeijer, van’t Veer & den Nijs 1994; Parker 2000; Koop & Horvitz 2005). As dune fixation proceeds further to fixed dunes with microbiotic crust, A. ordosica exhibits slow plant growth, limited seedling recruitment and a declining population growth, which are typical for populations in a ‘regressive’ stage (Oostermeijer, van’t Veer & den Nijs 1994; Parker 2000; Koop & Horvitz 2005). This decline in population growth reflects a succession tendency over the course of the dune fixation process, which indicates that this species will gradually lose its dominance as the dune gets more fixed, although it may still have high abundance temporally due to longevity of already established individuals. Also, the decline in A. ordosica’s abundance can be partly buffered by demographic adaptations, such as size shrinkage in later dune fixation stages.

In conclusion, the population dynamics of A. ordosica showed strong variation along stages of dune fixation, mainly due to differences in recruitment success and the incidence of shrinkage. The adaptive changes in life history traits of A. ordosica over the course of the dune fixation process may explain its dominance in the vast inland dune area of Mu Us Sandland.

Acknowledgements

We thank Dr. Feike Schieving and Dr. Heinjo During for help with statistical analysis, Mr. Chang-Yuan Li for assistance with field work and two anonymous reviewers for valuable comments on an early version of the manuscript. This research was supported by a CAS-grant (kzcx2-yw-431-4), NSFC (31070371, 30770357, 30521005), a CAS-KNAW joint PhD Training Program, and the VEWALNE-project of State Key Lab of Vegetation and Environmental Change. P.A.Z. was supported by an ERC grant (242955).

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